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Vergleich von Kompetenzanforderungen an Business-Intelligence- und Big-Data-Spezialisten
16 references·1 citing·38 second hop
Vergleich von Kompetenzanforderungen an Business-Intelligence- und Big-Data-Spezialisten (2014)Vergleich von Kompetenzanforderungen an B…Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management (2013)Data Science, Predictive Anal…Data science and prediction (2013)Data science and predictionData Science and its Relationship to Big Data and Data-Driven Decision Making (2013)Data Science and its Relation…Big Data (2013)Big DataMotivating salespeople: what really works. (2012)Motivating salespeople: what …Business Intelligence and Analytics: From Big Data to Big Impact (2012)Business Intelligence and Ana…Big Data analytics (2012)Big Data analyticsBusiness Intelligence Maturity: Development and Evaluation of a Theoretical Model (2011)Business Intelligence Maturit…Big data: The next frontier for innovation, competition, and productivity (2011)Big data: The next frontier f…Latent Semantic Analysis: five methodological recommendations (2010)Latent Semantic Analysis: fiv…Uncovering the Intellectual Core of the Information Systems Discipline1 (2008)Uncovering the Intellectual C…Uncovering the intellectual core of the information systems discipline (2008)Uncovering the intellectual c…A brief history of decision support systems (2007)A brief history of decision s…Competing on analytics. (2006)Competing on analytics.Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value1 (2004)Review: Information Technolog…Firm resources and sustained competitive advantage (2004)Firm resources and sustained …Kontext und KI: Zum Potenzial der Beschäftigten für Künstliche Intelligenz und Machine-Learning (2020)Kontext und KI: Zum Potenzial…Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? (2011)Big Data’s End Run around Anonymity and Consent (2014)Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective (2015)Human resources for Big Data professions: A systematic classification of job roles and required skill sets (2017)A resource‐based view of the firm (1984)The cornerstones of competitive advantage: A resource‐based view (1993)The Theory of the Growth of the Firm (1995)Social Capital, Intellectual Capital, and the Organizational Advantage (1998)Dynamic capabilities: what are they? (2000)The Theory of Economic Development (2003)Big data: the management revolution. (2012)Critical analysis of Big Data challenges and analytical methods (2016)The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018)A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0 (2020)Firm Resources and Sustained Competitive Advantage (1991)Dynamic capabilities and strategic management (1997)Supply chain collaboration: Impact on collaborative advantage and firm performance (2010)A Guide to Conducting a Systematic Literature Review of Information Systems Research (2011)Synthesizing information systems knowledge: A typology of literature reviews (2014)Conjectures and Refutations (1963)To Explain or to Predict? (2010)Editorial —Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research (2014)Data Science (2017)How Social Media Facilitates Political Protest: Information, Motivation, and Social Networks (2018)Beyond the hype: Big data concepts, methods, and analytics (2014)Big Data: A Survey (2014)Data-intensive applications, challenges, techniques and technologies: A survey on Big Data (2014)Managing Customer Relationships in the Social Media Era: Introducing the Social CRM House (2013)Challenges and solutions for marketing in a digital era (2014)Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications (2014)Big Data: Survey, Technologies, Opportunities, and Challenges (2014)What is big data? A consensual definition and a review of key research topics (2015)Artificial intelligence in operations management and supply chain management: an exploratory case study (2021)Understanding Customer Experience Throughout the Customer Journey (2016)Digital transformation: A multidisciplinary reflection and research agenda (2019)Big data analytics capabilities: a systematic literature review and research agenda (2017)Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management (2017)Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience (2019)
this work references cited by second hop

References

  • 2004Firm resources and sustained competitive advantage38,157 cited
  • 2012Business Intelligence and Analytics: From Big Data to Big Impact6,241 cited
  • 2011Big data: The next frontier for innovation, competition, and productivity5,202 cited
  • 2004Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value13,379 cited
  • 2013Data Science and its Relationship to Big Data and Data-Driven Decision Making1,569 cited
  • 2013Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management1,518 cited
  • 2006Competing on analytics.994 cited
  • 2013Data science and prediction855 cited
  • 2012Big Data analytics753 cited
  • 2012Motivating salespeople: what really works.547 cited
  • 2007A brief history of decision support systems488 cited
  • 2008Uncovering the intellectual core of the information systems discipline424 cited
  • 2008Uncovering the Intellectual Core of the Information Systems Discipline1368 cited
  • 2010Latent Semantic Analysis: five methodological recommendations306 cited
  • 2013Big Data131 cited

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2011
Business Intelligence Maturity: Development and Evaluation of a Theoretical Model
122 cited

Cited by

  • 2020Kontext und KI: Zum Potenzial der Beschäftigten für Künstliche Intelligenz und Machine-Learning30 cited